code: def test_inference_masked_lm(self):
      model = TFMPNetModel.from_pretrained("microsoft/mpnet-base")
      input_ids = tf.constant([[0, 1, 2, 3, 4, 5]])
      output = model(input_ids)[0]
  
      expected_shape = [1, 6, 768]
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = tf.constant(
          [
              [
                  [-0.1067172, 0.08216473, 0.0024543],
                  [-0.03465879, 0.8354118, -0.03252288],
                  [-0.06569476, -0.12424111, -0.0494436],
              ]
          ]
      )
      tf.debugging.assert_near(
          output[:, :3, :3], expected_slice, atol=1e-4
      )
  
imports: import unittest
  from transformers import MPNetConfig, is_tf_available
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the TFMPNetModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm() without return types